Figure 1

Antigen persists in discrete stromal cell populations within the lymph node

  1. Experimental design
  2. Mean Ag-score is shown for each cell type for 2, 14, 21, and 42 days post vaccination.
  3. UMAP projection shows LEC subsets.
  4. UMAP projections show Ag-scores for LEC subsets for each timepoint.
  5. Mean Ag-score is shown for LEC subsets for each timepoint.
  6. Ag-scores are shown for each timepoint for each LEC subset.
  7. UMAP projection shows DC subsets.
  8. UMAP projections show Ag-scores for DC subsets for each timepoint.
  9. Mean Ag-score is shown for DC subsets for each timepoint.
  10. Ag-scores are shown for each timepoint for each DC subset.
  • Experiment 1 is shown for the LEC 21 and 42 day timepoints. Experiment 2 data include very few LECs for the 21 day timepoint.
  • Experiment 2 is shown for the DC 21 and 42 day timepoints. Experiment 1 data are lower quality (sparse signal, mostly zeros).
  • Subsets are only shown if there are >= 5 cells for each timepoint
  • CD45+ and CD45- cell types are only shown for the CD45+ and CD45- datasets, respectively.



Figure 2

Identification of an antigen archiving gene signature

  1. Ag-score is shown for day 14 Ag-high and -low cells identified for LEC subsets with the highest Ag-score.
  2. The fraction of cells predicted to be Ag-competent is shown for each LEC subset 14, 21, and 42 days post vaccination.
  3. Ag-high module score is shown for Ag-high and predicted Ag-competent LECs for each timepoint.
  4. UMAP projections show Ag-high module scores for cLECs for each timepoint.
  5. The expression of select genes from the Ag-high (top) and Ag-low (bottom) modules is shown.
  • Ag-low and -high cells were identified by separately clustering each d14 LEC subset for each sample into two groups based on Ag-score.
  • The cutoffs identified for the d14 dataset were then used to identify Ag-high cells for the other timepoints.
  • With this approach there is a different cutoff for each LEC subset, but the cutoff is consistent across timepoints.



Figure 3

  • p-values were calculated using a t test with bonferroni correction



Figure 4



Figure 5



Session info

## R version 4.3.1 (2023-06-16)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.3 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 
## LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so;  LAPACK version 3.10.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8          LC_NUMERIC=C                 
##  [3] LC_TIME=en_US.UTF-8           LC_COLLATE=en_US.UTF-8       
##  [5] LC_MONETARY=en_US.UTF-8       LC_MESSAGES=en_US.UTF-8      
##  [7] LC_PAPER=en_US.UTF-8          LC_NAME=en_US.UTF-8          
##  [9] LC_ADDRESS=en_US.UTF-8        LC_TELEPHONE=en_US.UTF-8     
## [11] LC_MEASUREMENT=en_US.UTF-8    LC_IDENTIFICATION=en_US.UTF-8
## 
## time zone: America/Denver
## tzcode source: system (glibc)
## 
## attached base packages:
##  [1] stats4    tools     grid      stats     graphics  grDevices utils    
##  [8] datasets  methods   base     
## 
## other attached packages:
##  [1] ggtree_3.8.2          GOSemSim_2.26.1       org.Mm.eg.db_3.17.0  
##  [4] AnnotationDbi_1.62.2  IRanges_2.34.1        S4Vectors_0.38.2     
##  [7] Biobase_2.60.0        BiocGenerics_0.46.0   msigdbr_7.5.1        
## [10] enrichplot_1.20.3     clusterProfiler_4.8.3 caret_6.0-94         
## [13] lattice_0.21-8        furrr_0.3.1           future_1.33.0        
## [16] ranger_0.15.1         rsample_1.2.0         harmony_1.1.0        
## [19] biomaRt_2.56.1        openxlsx_4.2.5.2      MetBrewer_0.2.0      
## [22] ggtext_0.1.2          ggtrace_0.2.0.9000    qs_0.25.5            
## [25] vroom_1.6.4           M3Drop_1.26.0         numDeriv_2016.8-1.1  
## [28] djvdj_0.1.0           gtools_3.9.4          clustifyrdata_1.1.0  
## [31] here_1.0.1            presto_1.0.0          data.table_1.14.8    
## [34] Rcpp_1.0.11           devtools_2.4.5        usethis_2.2.2        
## [37] ComplexHeatmap_2.16.0 patchwork_1.1.3       scales_1.2.1         
## [40] boot_1.3-28.1         clustifyr_1.12.0      mixtools_2.0.0       
## [43] broom_1.0.5           colorblindr_0.1.0     colorspace_2.1-0     
## [46] xlsx_0.6.5            RColorBrewer_1.1-3    ggrepel_0.9.3        
## [49] cowplot_1.1.1         knitr_1.44            gprofiler2_0.2.2     
## [52] SeuratObject_4.1.4    Seurat_4.4.0          ggforce_0.4.1        
## [55] ggbeeswarm_0.7.2      lubridate_1.9.3       forcats_1.0.0        
## [58] stringr_1.5.0         dplyr_1.1.3           purrr_1.0.2          
## [61] readr_2.1.4           tidyr_1.3.0           tibble_3.2.1         
## [64] ggplot2_3.4.4         tidyverse_2.0.0      
## 
## loaded via a namespace (and not attached):
##   [1] igraph_1.5.1                ica_1.0-3                  
##   [3] plotly_4.10.2               Formula_1.2-5              
##   [5] zlibbioc_1.46.0             tidyselect_1.2.0           
##   [7] bit_4.0.5                   doParallel_1.0.17          
##   [9] clue_0.3-65                 rjson_0.2.21               
##  [11] blob_1.2.4                  urlchecker_1.0.1           
##  [13] S4Arrays_1.0.6              parallel_4.3.1             
##  [15] png_0.1-8                   cli_3.6.1                  
##  [17] ggplotify_0.1.2             goftest_1.2-3              
##  [19] kernlab_0.9-32              densEstBayes_1.0-2.2       
##  [21] uwot_0.1.16                 shadowtext_0.1.2           
##  [23] curl_5.1.0                  mime_0.12                  
##  [25] evaluate_0.22               tidytree_0.4.5             
##  [27] leiden_0.4.3                stringi_1.7.12             
##  [29] pROC_1.18.5                 backports_1.4.1            
##  [31] XML_3.99-0.14               httpuv_1.6.11              
##  [33] magrittr_2.0.3              rappdirs_0.3.3             
##  [35] splines_4.3.1               prodlim_2023.08.28         
##  [37] RApiSerialize_0.1.2         ggraph_2.1.0               
##  [39] sctransform_0.4.0           sessioninfo_1.2.2          
##  [41] DBI_1.1.3                   jquerylib_0.1.4            
##  [43] withr_2.5.1                 class_7.3-22               
##  [45] rprojroot_2.0.3             lmtest_0.9-40              
##  [47] bdsmatrix_1.3-6             tidygraph_1.2.3            
##  [49] htmlwidgets_1.6.2           fs_1.6.3                   
##  [51] SingleCellExperiment_1.22.0 segmented_1.6-4            
##  [53] labeling_0.4.3              MatrixGenerics_1.12.3      
##  [55] reticulate_1.32.0           zoo_1.8-12                 
##  [57] XVector_0.40.0              timechange_0.2.0           
##  [59] foreach_1.5.2               fansi_1.0.5                
##  [61] caTools_1.18.2              timeDate_4022.108          
##  [63] irlba_2.3.5.1               gridGraphics_0.5-1         
##  [65] ellipsis_0.3.2              lazyeval_0.2.2             
##  [67] yaml_2.3.7                  survival_3.5-5             
##  [69] scattermore_1.2             crayon_1.5.2               
##  [71] RcppAnnoy_0.0.21            progressr_0.14.0           
##  [73] tweenr_2.0.2                later_1.3.1                
##  [75] ggridges_0.5.4              codetools_0.2-19           
##  [77] base64enc_0.1-3             GlobalOptions_0.1.2        
##  [79] profvis_0.3.8               KEGGREST_1.40.1            
##  [81] bbmle_1.0.25                Rtsne_0.16                 
##  [83] shape_1.4.6                 filelock_1.0.2             
##  [85] foreign_0.8-84              pkgconfig_2.0.3            
##  [87] xml2_1.3.5                  GenomicRanges_1.52.1       
##  [89] aplot_0.2.2                 spatstat.sparse_3.0-2      
##  [91] ape_5.7-1                   viridisLite_0.4.2          
##  [93] xtable_1.8-4                plyr_1.8.9                 
##  [95] httr_1.4.7                  globals_0.16.2             
##  [97] hardhat_1.3.0               pkgbuild_1.4.2             
##  [99] beeswarm_0.4.0              htmlTable_2.4.2            
## [101] checkmate_2.3.0             nlme_3.1-162               
## [103] loo_2.6.0                   HDO.db_0.99.1              
## [105] dbplyr_2.3.4                digest_0.6.33              
## [107] Matrix_1.6-1.1              farver_2.1.1               
## [109] tzdb_0.4.0                  reshape2_1.4.4             
## [111] ModelMetrics_1.2.2.2        yulab.utils_0.1.0          
## [113] viridis_0.6.4               rpart_4.1.19               
## [115] glue_1.6.2                  cachem_1.0.8               
## [117] BiocFileCache_2.8.0         polyclip_1.10-6            
## [119] Hmisc_5.1-1                 generics_0.1.3             
## [121] Biostrings_2.68.1           mvtnorm_1.2-3              
## [123] parallelly_1.36.0           pkgload_1.3.3              
## [125] statmod_1.5.0               pbapply_1.7-2              
## [127] SummarizedExperiment_1.30.2 gson_0.1.0                 
## [129] utf8_1.2.3                  gower_1.0.1                
## [131] graphlayouts_1.0.2          StanHeaders_2.26.28        
## [133] gridExtra_2.3               shiny_1.7.5                
## [135] lava_1.7.3                  GenomeInfoDbData_1.2.10    
## [137] RCurl_1.98-1.12             memoise_2.0.1              
## [139] rmarkdown_2.25              downloader_0.4             
## [141] RANN_2.6.1                  stringfish_0.15.8          
## [143] spatstat.data_3.0-1         rstudioapi_0.15.0          
## [145] cluster_2.1.4               QuickJSR_1.0.7             
## [147] rstantools_2.3.1.1          spatstat.utils_3.0-3       
## [149] hms_1.1.3                   fitdistrplus_1.1-11        
## [151] munsell_0.5.0               rlang_1.1.1                
## [153] GenomeInfoDb_1.36.4         ipred_0.9-14               
## [155] circlize_0.4.15             mgcv_1.8-42                
## [157] xfun_0.40                   remotes_2.4.2.1            
## [159] recipes_1.0.8               iterators_1.0.14           
## [161] matrixStats_1.0.0           reldist_1.7-2              
## [163] abind_1.4-5                 rstan_2.32.3               
## [165] treeio_1.24.3               rJava_1.0-6                
## [167] bitops_1.0-7                ps_1.7.5                   
## [169] promises_1.2.1              inline_0.3.19              
## [171] scatterpie_0.2.1            RSQLite_2.3.1              
## [173] qvalue_2.32.0               fgsea_1.26.0               
## [175] DelayedArray_0.26.7         GO.db_3.17.0               
## [177] compiler_4.3.1              prettyunits_1.2.0          
## [179] listenv_0.9.0               tensor_1.5                 
## [181] MASS_7.3-60                 progress_1.2.2             
## [183] BiocParallel_1.34.2         gridtext_0.1.5             
## [185] babelgene_22.9              spatstat.random_3.1-6      
## [187] R6_2.5.1                    fastmap_1.1.1              
## [189] fastmatch_1.1-4             vipor_0.4.5                
## [191] ROCR_1.0-11                 nnet_7.3-19                
## [193] gtable_0.3.4                KernSmooth_2.23-21         
## [195] miniUI_0.1.1.1              deldir_1.0-9               
## [197] htmltools_0.5.6.1           RcppParallel_5.1.7         
## [199] bit64_4.0.5                 spatstat.explore_3.2-3     
## [201] lifecycle_1.0.3             zip_2.3.0                  
## [203] processx_3.8.2              callr_3.7.3                
## [205] xlsxjars_0.6.1              sass_0.4.7                 
## [207] vctrs_0.6.3                 spatstat.geom_3.2-5        
## [209] DOSE_3.26.2                 ggfun_0.1.3                
## [211] sp_2.1-0                    future.apply_1.11.0        
## [213] entropy_1.3.1               bslib_0.5.1                
## [215] pillar_1.9.0                gplots_3.1.3               
## [217] jsonlite_1.8.7              GetoptLong_1.0.5